Vision systems are commonly used within vehicles for automatic control and monitoring of vehicle equipment. More specially, a camera is integrated into an auto-dimming mirror and combined with algorithmic decision making processing to automatically operate vehicle high beam headlamps in order to optimize their usage according to surrounding traffic conditions. In order for the vision system to operate properly, it is important that the camera used in the vision system to be accurately aligned. To ensure that the camera is accurately aligned, auto aiming algorithms constantly measure and correct imager misalignment over time. There are generally two types of auto aiming algorithms, viz. tail light aim and lane line aim. Both types of aim algorithms use weighted averaging to help reduce outlier data points and more accurately converge on a center point of the camera.
In use, if a vehicle windshield angle is different from the calibrated center point, then a “windshield offset” value is used to initially adjust the vertical center point calibrating the vision system camera in the vehicle. Although alignment often occurs during the manufacture of the vehicle, while it is in operation, the vision system must even more accurately align the camera especially in the horizontal plane. Accordingly, new systems and processes are required to insure that the system provides only the most accurate information to the headlight control so the driver has the best vision available for current road and environmental conditions.
The present invention provides improvements in vehicle vision system components, vehicle vision systems and vehicle equipment control systems employing the vision system components and vision systems.